Abstract
Recall that the aim of data reduction is to reduce (without using the outcome) the number of parameters needed in the outcome model.
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Notes
- 1.
The spca package is a new sparse PC package that should also be considered.
References
H. Ahn and W. Loh. Tree-structured proportional hazards regression modeling. Biometrics, 50:471–485, 1994.
D. F. Andrews and A. M. Herzberg. Data. Springer-Verlag, New York, 1985.
L. Breiman and J. H. Friedman. Estimating optimal transformations for multiple regression and correlation (with discussion). J Am Stat Assoc, 80:580–619, 1985.
D. P. Byar and S. B. Green. The choice of treatment for cancer patients based on covariate information: Application to prostate cancer. Bulletin Cancer, Paris, 67:477–488, 1980.
D. R. Cox. Regression models and life-tables (with discussion). J Roy Stat Soc B, 34:187–220, 1972.
E. R. Dickson, P. M. Grambsch, T. R. Fleming, L. D. Fisher, and A. Langworthy. Prognosis in primary biliary cirrhosis: Model for decision making. Hepatology, 10:1–7, 1989.
P. Filzmoser, H. Fritz, and K. Kalcher. pcaPP: Robust PCA by Projection Pursuit, 2012. R package version 1.9–48.
T. R. Fleming and D. P. Harrington. Counting Processes & Survival Analysis. Wiley, New York, 1991.
W. Hoeffding. A non-parametric test of independence. Ann Math Stat, 19:546–557, 1948.
I. T. Jolliffe. Principal Component Analysis. Springer-Verlag, New York, second edition, 2010.
C. Kooperberg, C. J. Stone, and Y. K. Truong. Hazard regression. J Am Stat Assoc, 90:78–94, 1995.
W. F. Kuhfeld. The PRINQUAL procedure. In SAS/STAT 9.2 User’s Guide. SAS Publishing, Cary, NC, second edition, 2009.
W. Sauerbrei and M. Schumacher. A bootstrap resampling procedure for model building: Application to the Cox regression model. Stat Med, 11:2093–2109, 1992.
M. Schemper and G. Heinze. Probability imputation revisited for prognostic factor studies. Stat Med, 16:73–80, 1997.
D. M. Witten and R. Tibshirani. Testing significance of features by lassoed principal components. Ann Appl Stat, 2(3):986–1012, 2008.
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Harrell, F.E. (2015). Case Study in Data Reduction. In: Regression Modeling Strategies. Springer Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-19425-7_8
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